The present disclosure relates to measuring a user's body signals, and more particularly, to a system and method for providing a real-time signal segmentation and fiducial points alignment framework.
As with any portable electronic device, it is desirable for a wearable sensor device that monitors biosignals to accurately detect desired biosignals. However, motions of the user, complexity of detected signals, and noise in the detected signals can make accurate detection of biosignals challenging.
Conventional beat detection methods are typically used to determine health measurements (e.g., heart rate, respiration rate) from various types of measurement sensors. These measurement sensors measure different types of sensor signals such as, for example, ballistocardiography (BCG) signals, photoplethysmogram (PPG) signals, electrocardiogram (ECG) signals, galvanic skin response (GSR) signals, and bio-impedance signals. Such conventional beat detection methods are not able to provide accurate detection performance and reliably identify feature points on a noisy signal.